Evidence map›Paper›PMID 28984872›Full record

ReviewCell death and differentiation2018

p53 shades of Hippo.

Noa Furth, Yael Aylon, Moshe Oren

Abstract readReview
In one paragraph

Review in Cell death and differentiation, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

61 citing papers in PubMed.

  1. Article
  2. Observational
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1 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Noa FurthDepartment of Molecular Cell Biology, The Weizmann Institute, Rehovot, Israel.
Yael AylonDepartment of Molecular Cell Biology, The Weizmann Institute, Rehovot, Israel.
Moshe OrenDepartment of Molecular Cell Biology, The Weizmann Institute, Rehovot, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The three p53 family members, p53, p63 and p73, are structurally similar and share many biochemical activities. Yet, along with their common fundamental role in protecting genomic fidelity, each has acquired distinct functions related to diverse cell autonomous and non-autonomous processes. Similar to the p53 family, the Hippo signaling pathway impacts a multitude of cellular processes, spanning from cell cycle and metabolism to development and tumor suppression. The core Hippo module consists of the tumor-suppressive MST-LATS kinases and oncogenic transcriptional co-effectors YAP and TAZ. A wealth of accumulated data suggests a complex and delicate regulatory network connecting the p53 and Hippo pathways, in a highly context-specific manner. This generates multiple layers of interaction, ranging from interdependent and collaborative signaling to apparent antagonistic activity. Furthermore, genetic and epigenetic alterations can disrupt this homeostatic network, paving the way to genomic instability and cancer. This strengthens the need to better understand the nuances that control the molecular function of each component and the cross-talk between the different components. Here, we review interactions between the p53 and Hippo pathways within a subset of physiological contexts, focusing on normal stem cells and development, as well as regulation of apoptosis, senescence and metabolism in transformed cells.

Indexed as

AnimalsApoptosisCarcinogenesisCellular SenescenceHumansNeoplastic Stem CellsPloidiesProtein Serine-Threonine KinasesSignal TransductionStem CellsTranscription FactorsTumor Suppressor Protein p53Protein Serine-Threonine KinasesTranscription FactorsTumor Suppressor Protein p53

Identifiers

PMID28984872
PMCPMC5729527

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.